Senior Vice President, Software Engineering

Engg; O’Fallon (MO); On-site; USD 300,000 - 500,000; Full time

Job summary

Mastercard is seeking an Engineering Co-Founder to lead the Decision Stream platform, blending startup agility with enterprise rigor. You will shape the engineering vision, architecture, and talent strategy to deliver real-time decisioning at scale.

You will partner with Product, AI, and Foundry teams to align investments with customer outcomes and drive a culture of ownership, speed, and accountability across globally distributed teams.

Qualifications

• Engineering leadership experience with large-scale platforms.
• Proven ability to scale distributed systems with high availability.
• Deep expertise in cloud-native architectures and microservices.

Responsibilities

• Lead the engineering vision for Decision Stream and partner with product and AI teams.
• Drive platform delivery, MVP validation, and scalable deployment at enterprise scale.
• Establish governance, metrics, and an operating rhythm for high performance.

Skills

Engineering leadership

Distributed systems

Cloud-native architecture

Microservices

Executive communication

Tools

Kafka

Flink

Job description

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Senior Vice President, Software Engineering Senior Vice President, Software Engineering – Decision Stream Engineering Co-Founder

Job Description Summary

Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Overview

Decision Stream is Mastercard's next-generation, AI-native decisioning platform designed to deliver intelligent, real-time decisioning across payments, fraud, authentication, and adjacent risk domains. The platform is being built as a startup-style venture within Mastercard, combining the speed and innovation of a product startup with the scale, security, and reach of an enterprise platform. We are seeking an Engineering Co-Founder to lead the engineering vision, architecture execution, talent strategy, and platform delivery for Decision Stream. This leader will partner closely with Product, Architecture, AI, Platform, and Foundry teams to build an industry-leading, cloud-native decisioning platform that redefines how decisions are made across Mastercard's ecosystem.

Engineering Leadership & Strategy

• Establish and execute the engineering vision for Decision Stream.
• Drive engineering priorities, technical investment decisions, and platform evolution.
• Create a high-performance culture built on ownership, innovation, accountability, and speed.
• Partner with executive leadership to define long-term technology strategy and roadmap.

Platform & Architecture

• Lead the development of a cloud-native, AI-native decisioning platform capable of operating at Mastercard scale.
• Drive architectural decisions across streaming, orchestration, rules execution, AI inference, observability, resiliency, and platform services.
• Ensure platform reliability, scalability, security, and operational excellence.
• Balance rapid experimentation with enterprise-grade engineering discipline.

Talent & Organization

• Build and scale world-class engineering teams across platform engineering, AI, distributed systems, and product development.
• Develop a lean operating model built around empowered cross-functional pods.

Product & Business Partnership

• Partner closely with the Product Co-Founder to align engineering investments with customer outcomes and business objectives.
• Work collaboratively across Product, Architecture, Foundry, Operations, and AI teams as one integrated leadership team.
• Drive a culture where engineering teams own outcomes.

Execution & Delivery

• Lead the platform through MVP validation, commercialization readiness, and scaled adoption.
• Establish engineering metrics, governance, and operating rhythms.
• Drive rapid iteration cycles focused on learning, experimentation, and measurable outcomes.
• Remove organizational barriers and accelerate decision making across teams.
• Create an environment where innovation and accountability coexist.

Qualifications

Leadership Expectations

• Operate as an entrepreneur and builder.
• Demonstrate bias for action and comfort with ambiguity.
• Make decisions quickly using data and customer insights.
• Foster radical transparency and cross-functional collaboration.
• Inspire teams through vision, technical credibility, and execution excellence.
• Challenge conventional thinking while remaining focused on business outcomes.

Required

• Engineering leadership experience.
• Proven experience building and scaling large-scale distributed platforms.
• Deep expertise in cloud-native architecture, microservices, event-driven systems, and modern software engineering practices.
• Demonstrated success leading engineering organizations through transformation and growth.
• Experience delivering platforms requiring high availability, resiliency, and performance at significant scale.
• Strong executive communication and stakeholder management skills.

Preferred

• Experience with AI/ML product platforms and intelligent decisioning systems.
• Expertise in streaming technologies such as Kafka, Flink, or similar event-processing architectures.
• Experience in payments, fraud, risk, authentication, or financial services technology.
• Background building startup ventures, innovation labs, or greenfield platforms.
• Record of leading globally distributed engineering organizations.

Corporate Security Responsibility

• Abide by Mastercard’s security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Total Base Pay Ran